The study investigates the intricate dynamics of SARS-CoV-2 transmission, with a particular focus on both close-contact interactions and environmental factors. Using advanced mathematical modeling and epidemiological analysis, explored the effects of these transmission pathways on the spread of COVID-19. The equilibrium points for both the disease-free and endemic states calculated and evaluated their global stability. Additionally, the basic reproduction number (R0) is derived to quantify the transmission potential of the virus. To ensure model accuracy, numerical simulations are performed using MATLAB, utilizing daily COVID-19 case data from India. Parameter values are sourced from existing literature, with certain parameters estimated through fitting the model to observed data. Crucially, the model incorporates environmental transmission factors, such as surface contamination and airborne spread. The inclusion of these factors provides a more comprehensive understanding of the virus's spread, demonstrating the importance of interventions like use of face masks, environmental sanitization, vaccine efficacy, availability of treatment resources underappreciated when focusing solely on direct human contact. A sensitivity analysis is conducted to assess the impact of different parameters on R0, with results visualized through heat maps to identify the most influential factors. Furthermore, Pontryagin's maximum principle is employed to develop an optimal control model, enabling the formulation of effective intervention strategies. By analysing both interpersonal and environmental transmission mechanisms, this study offers a more holistic framework for understanding SARS-CoV-2 transmission. The insights gained are critical for informing public health strategies, emphasizing the necessity of addressing both direct contact and environmental sources of infection to more effectively manage current and future outbreaks.
Introduction: Hepatocellular Carcinoma (HCC) is a common malignant tumor worldwide. Long Non-Coding RNA (lncRNA) has gained attention in tumor biology, and this study aims to investigate the role of lncRNA SNHG3 in HCC, specifically in the self-renewal and maintenance of liver cancer stem cells.
Methods: The expression of lncRNA SNHG3 was analyzed in HCC and adjacent normal tissue using the TCGA database. The expression levels of SNHG3 in HCC cell lines (Hep3B, HepG2, Huh7) were detected using qRT-PCR and Western blot techniques. Functional assays, including CCK-8, soft agar colony formation, and tumor sphere formation, were performed to evaluate the impact of SNHG3 on HCC stem cell functionality. MeRIP-qPCR was also used to investigate the regulatory role of SNHG3 in m6A modification of ITGA6 mRNA mediated by METTL3.
Results: The study found that SNHG3 was significantly upregulated in HCC tissue and cell lines compared to normal liver tissue. SNHG3 expression correlated with the pathological stage, metastasis status, and tumor size of liver cancer. Inhibiting SNHG3 reduced proliferation, colony formation, and tumor sphere formation ability in HCC stem cells. SNHG3 also played a role in regulating the m6A modification and expression of ITGA6 through METTL3.
Conclusion: This study emphasizes the upregulation of lncRNA SNHG3 and its role in HCC stem cell self-renewal. SNHG3 may regulate the m6A modification of ITGA6 mRNA through its interaction with METTL3, impacting the function of liver cancer stem cells. These findings support the potential of targeting SNHG3 as a therapeutic approach for HCC.
Sustainability in dairy cattle farms depends on the efficiency of milk yield and reproductive traits. Thus, this study aimed to investigate the effect of the FGF-2/Csp6I gene and major environmental factors on these traits in Holstein-Friesian cattle. A total of 212 whole blood samples were collected from the Vena coccygea of cattle and the data obtained from these samples were used in all statistical analyses. Then, the restriction fragment length polymorphism (RFLP) method (determination of genotypes) was conducted and programs including PopGene (allele and genotype frequencies), Minitab (association analyses) and MTDFREML (variance components and genetic parameters) were used. Alleles A (0.4269) and G (0.5731) as well as genotypes AA (0.174), AG (0.505) and GG (0.321) were found, indicating that the population is polymorphic and in Hardy-Weinberg equilibrium (P > 0.05). The effect of the Csp6I polymorphism of FGF-2 gene on peak milk yield (PMY) (P < 0.01); lactation milk yield (LMY), milking time (MT), 305-day and 200-day lactation milk yield (LMY305 and LMY200), average daily milk yield (ADMY) (P < 0.05); 100-day lactation milk yield (LMY100), age of using in first breeding (AUFB) and number of inseminations per conception (NIPC) (P < 0.10) were significant. The heritability of milk yield traits and the correlation between direct and maternal heritability for reproductive traits were high. Furthermore, the breeding value of PMY was higher for the AA genotype (0.745 ± 0.292) than for the AG genotype (-0.268 ± 0.171) (P < 0.05). As a result, the A allele and AA genotype for the FGF-2/Csp6I gene had an increasing effect on milk yield without compromising reproductive performance in Holstein-Friesian dairy cattle.